Calculating popularity quantiles
You're continuing to analyze the Spotify dataset containing 25 popular albums with metrics like streams, monthly_listeners, and popularity. The marketing team needs clear tiers for underperforming, typical, and breakout albums. Calculate percentiles to help the team understand how popularity is distributed.
polars is loaded as pl. The DataFrame spotify with streaming metrics is preloaded for you.
Deze oefening maakt deel uit van de cursus
Data Transformation with Polars
Oefeninstructies
- Select the
popularitycolumn and calculate the 25th percentile, aliasing it asq25_popularity. - Add the 50th and 75th percentiles to the appropriate aliases.
Praktische interactieve oefening
Probeer deze oefening eens door deze voorbeeldcode in te vullen.
# Calculate the 25th, 50th, and 75th percentiles of popularity
result = spotify.select(
pl.col("____").____(0.25).alias("q25_popularity"),
pl.col("popularity").quantile(____).alias("q50_popularity"),
pl.col("popularity").quantile(____).alias("q75_popularity"),
)
print(result)